Pavel Kireyev

Pavel Kireyev is an Assistant Professor of Marketing at INSEAD. He conducts research with data-driven companies and studies innovative marketing technologies, platforms, and marketplaces. Prior to joining INSEAD, he led projects on the development of machine learning algorithms at a startup, formed partnerships with corporate artificial intelligence labs, and worked as a data scientist with large organizations in the US and Japan.

Pavel uses modern quantitative methods to uncover how organizations can effectively coordinate their pricing and advertising strategies across multiple platforms, benefit from new resources such as crowd intelligence, and manage behavioral data to improve decision-making and market design in multi-sided marketplaces. He has published research in academic journals on quantitative marketing and presented at several business schools and international conferences. He holds a Doctorate in Business Administration from the Harvard Business School, an MA in Statistics from Yale University, and a BSc in Business Mathematics and Statistics from the London School of Economics.

Research Areas

• Marketing Technology
• Digital Platforms
• Marketplaces
• Behavioural Data

Teaching Areas

• Artificial Intelligence Strategy (MBA)
• Advanced Multivariate Statistics (PhD)

Education

• Doctor of Business Administration (DBA) - Harvard Business School
• Master of Arts (MA) - Yale University
• Bachelor of Science (BSc) - The London School of Economics and Political Science (LSE)

Journal Articles

• Kireyev P., Evans P. C. (2021). Making Sense of the NFT Marketplace . Harvard Business Review Digital Articles
• Kireyev P. (2020). Markets for Ideas: Prize Structure, Entry Limits, and the Design of Ideation Contests . Rand Journal of Economics, 51(2), pp563-588.
• Kireyev P., Kumar V., Ofek E. (2017). Match Your Own Price? Self-Matching as a Retailer’s Multichannel Pricing Strategy. Marketing Science, 36(6), pp908-930.
• Kireyev P., Pauwels K., Gupta S. (2016). Do Display Ads Influence Search? Attribution and Dynamics in Online Advertising. International Journal of Research in Marketing, 33(3), pp475-490.